In conventional systems, information about a user (e.g., the programs, movies, genres, etc. that a user enjoys) is often tracked. The tracked information, typically contained in a user profile, may then be used by a wide variety of entities to suggest or recommend content.
Despite the widespread use of tracking user information, the way the information is gathered is very reactionary. For example, in conventional systems, content a user has previously watched is used to determine content a user would like to watch. As the user begins watching different content (e.g., different television shows), the user profile gradually changes to reflect the different content. Therefore, the user profile in conventional systems is a better indicator of content that a user has previously preferred, not content that a user currently prefers or will prefer.